“Cloud computing” is fast becoming a viable computing model for both small and large enterprises. The “cloud” typifies a computing style ill which dynamically scalable and often virtualized resources are provided as a service over the Internet. The term itself is a metaphor. As is known, the cloud infrastructure permits treating computing resources as utilities automatically provisioned on demand while the cost of service is strictly based on the actual resource consumption. Consumers of the resource also leverage technologies from the cloud that might not otherwise be available to them, in house, absent the cloud environment.
As with any new paradigm, considerable discussion is taking place regarding how best to utilize the environment. As one example, there has been recent interest in leveraging the public/private cloud infrastructure to make portable workloads of traditional data centers. To better explain this, consider a traditional data center workload operating on its associated data. (Assume here that the workload specific data is located in a single file with the workload executing on a single machine.) By “virtualizing” the workload, however, it can be hosted anywhere on any appropriate hardware. In turn, as the workload is migrated from one physical machine to another, the workload needs access to its associated data no matter where it is located. While a traditional data center solves this problem by hosting data via a storage area network (SAN) or a network file system that permits access to the data in a secure fashion independent of which physical machine the workload is hosted, this is not possible with present cloud architectures.
Furthermore, the size of the data and other security concerns may preclude co-locating the data with the workload. For instance, it is not uncommon for large enterprises to have terabytes of valuable data, such as sales information. Enterprises are then loathe to host the data in a cloud environment where it might be copied or lost and moving back and forth terabytes of data from a home location to the cloud is infeasible because of transmission bandwidth concerns and latency effects.
Accordingly, a need exists for better managing data for consumption by workloads. The need further contemplates data management in support of portable workloads, including minimizing bandwidth requirements for data migration while simultaneously shielding the workload from the latency of migrating it. Even more, the need should extend to securely vending the data for consumption. Any improvements along such lines should contemplate good engineering practices, such as simplicity, ease of implementation, unobtrusiveness, stability, etc.